Radiographic imaging techniques such as x-ray imaging have been used for years in medical applications and for non-destructive testing.
Normally, an x-ray imaging system includes an x-ray source and an x-ray detector consisting of multiple detector elements. The x-ray source emits x-rays, which pass through a subject or object to be imaged and are then registered by the detector. Since some materials absorb a larger fraction of the x-rays than others, an image is formed of the subject or object.
Conventional x-ray detectors are energy integrating, the contribution from each detected photon to the detected signal is therefore proportional to its energy, and in conventional CT, measurements are acquired for a single effective energy. The images produced by a conventional CT system therefore have a certain look, where different tissues and materials show typical values in certain ranges. Spectral CT is a collective term for CT imaging technologies that acquire measurement data at multiple effective energies. The energy information in spectral CT data allows for new kinds of images to be created, where new information is available and image artifacts inherent to conventional technology can be removed.
In order to draw upon the knowledge and rules-of-thumb accumulated from years of experience using conventional equipment, it would be desirable to along with new images, produce a single image from spectral CT data that mimics the characteristics of conventional CT images.
In the prior art there exist methods that use image-blending techniques for other purposes, such as optimizing contrast-to-noise ratio or detectability for a given task [4, 5]. A method with the same aim as the method presented in this work was presented in [3], but lacked a crucial step for accurate results.